collaborators

5 papers

cs.NI2026

Hardware-Aware Neural Architecture Search for Encrypted Traffic Classification on Resource-Constrained Devices

Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1

This paper presents a hardware-efficient deep neural network (DNN), optimized through hardware-aware neural architecture search (HW-NAS); the DNN supports the classification of ses…

cs.NI2025

Adversarial Robustness of Traffic Classification under Resource Constraints: Input Structure Matters

Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1

Traffic classification (TC) plays a critical role in cybersecurity, particularly in IoT and embedded contexts, where inspection must often occur locally under tight hardware constr…

cs.NI2025

Intrusion Detection on Resource-Constrained IoT Devices with Hardware-Aware ML and DL

Ali Diab, Adel Chehade, Edoardo Ragusa +4

This paper proposes a hardware-aware intrusion detection system (IDS) for Internet of Things (IoT) and Industrial IoT (IIoT) networks; it targets scenarios where classification is…

cs.NI2025

Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers

Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1

In this paper, we present a practical deep learning (DL) approach for energy-efficient traffic classification (TC) on resource-limited microcontrollers, which are widely used in Io…

cs.NI2025

Tiny Neural Networks for Session-Level Traffic Classification

Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1

This paper presents a system for session-level traffic classification on endpoint devices, developed using a Hardware-aware Neural Architecture Search (HW-NAS) framework. HW-NAS op…